Six IU Bloomington researchers receive nearly $150,000 from translational research grant program

Six Indiana University Bloomington researchers across several academic disciplines and their teams have received grants from a program that supports developing translational research projects with industry, establishing new companies or strengthening patent applications.

Launched in 2015, the Translational Research Pilot Grant program funds the completion of proof-of-concept projects. The grants are offered by the Johnson Center for Innovation and Translational Research, which is part of the IU Innovation and Commercialization Office.

Submitted projects were based on discoveries that had been disclosed to IU ICO. Individual project budgets up to $25,000 were considered. The recipients, their project titles and funding amounts are as follows.

The project is to understand the utility of an online platform that promotes school safety to address student bullying. The service allows students to recognize what bullying is and isn't, to self-identify places and times bullying is happening at school, and to electronically set up an appointment to meet with a school counselor.

Brown said the funding has supported and strengthened the project in several ways.

"The team -- John M. Keesler and me -- commissioned a regional expert to create culture- and gender-specific videos with youth narrators as a fundamental element of the project," he said. "It also helped to secure other stakeholders and community partners, like school counselors who will introduce students to the platform, and be able to respond to them."

The goal of the project is to identify biomarkers that assess the efficacy of agents in modulating neuroinflammatory responses. The agents could slow down neurodegenerative conditions like Alzheimer's disease.

Lu said the funding will help her and her colleagues in two ways.

"First, it will enable us to validate experimentally in silico miR-142 targets with cell-based assays," Lu said. "Second, it will be used to determine how mRNA levels of miR-142 targets are regulated. Promising results will stimulate the development of miR-142 mimics as an RNA-based therapy for inflammatory and neurodegenerative diseases."

The goal of the project is to develop a prototype software data package to apply the Bayesian statistical method to model categorical dose-response data, which has an important translational application in chemical risk assessment.

Shao said the funding will strengthen his research team.

"The team will carry out the tasks of statistical methodology development and coding the program," he said. "The outcome from this project will provide a solid foundation for implementing the techniques in user-friendly, dose-response modeling software to support chemical risk assessment."

The goals are to enable post-Moore's Law computing by a performance gain beyond three orders of magnitude of conventional practices; to accelerate computations of dynamic graph data structures; and to empower real-time machine intelligence, including machine learning and understanding.

"It will be invaluable to the research and prototyping efforts performed by the CCA team, and it is the first equipment of that kind acquired by IU Bloomington," Sterling said. "If successful, Simultac will project a new trajectory of future computer system performance improvements throughout the next decade."

The goal of the project is to test several long-lasting drug candidates to treat glaucoma. The standard treatment is to take daily or twice-daily eye drops, but many patients stop taking the drops regularly. The rationale behind long-lasting drugs is that patients will be more likely to use the drugs if they only need to do so once a week.

Straiker said the funding will allow his team to get proof-of-concept data.

"If the drugs work as we hope they will, and the results so far are promising, it will put us in a good position to pursue this class of drugs as a therapeutic for glaucoma," Straiker said.

Haixu Tang, professor, Department of Informatics, School of Informatics, Computing and Engineering; adjunct professor, Department of Biology, College of Arts and Sciences: "Constrained De Novo Sequencing of Neo-epitope in Cancer Immunopeptideomics," $25,000.

The goal of the project is to develop a novel, constrained, de novo sequencing algorithm to identify neo-epitope peptides from proteomic data acquired in immunopeptidomic analyses.

"The funding will help us continue to develop and improve the algorithm, as well as allow us to provide integrated software for academic or commercial usage," Tang said.